Eco-friendly reduction of travel times in european smart cities

Daniel Stolfi, E. Alba
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引用次数: 12

Abstract

This article proposes an innovative solution for reducing polluting gas emissions from road traffic in modern cities. It is based on our new Red Swarm architecture which is composed of a series of intelligent spots with WiFi connections that can suggest a customized route to drivers. We have tested our proposal in four different case studies corresponding to actual European smart cities. To this end, we first import the city information from OpenStreetMap into the SUMO road traffic micro-simulator, propose a Red Swarm architecture based on intelligent spots located at traffic lights, and then optimize the resulting system in terms of travel times and gas emissions by using an evolutionary algorithm. Our results show that an important quantitative reduction in gas emissions as well as in travel times can be achieved when vehicles are rerouted according to our Red Swarm indications. This represents a promising result for the low cost implementation of an idea that could engage the interest of both citizens and municipal authorities.
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欧洲智慧城市的环保出行时间缩短
本文提出了一种减少现代城市道路交通污染气体排放的创新解决方案。它基于我们新的Red Swarm架构,该架构由一系列带有WiFi连接的智能点组成,可以为司机提供定制路线。我们已经在四个不同的案例研究中测试了我们的建议,这些案例对应于实际的欧洲智慧城市。为此,我们首先将OpenStreetMap中的城市信息导入到SUMO道路交通微模拟器中,提出了一种基于红绿灯智能点的Red Swarm架构,然后利用进化算法对生成的系统在出行时间和气体排放方面进行优化。我们的研究结果表明,当车辆根据我们的Red Swarm指示改变路线时,可以实现气体排放和行驶时间的重要定量减少。这代表了一个低成本实施的有希望的结果,这个想法可以吸引公民和市政当局的利益。
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